We aim to create a spatiotemporal single cell resolution map of the developing human neocortex in order to establish how many distinct cell types are present and to unravel their complex developmental history. We will build our analysis on a multimodal classification of cells types based on transcriptomic signatures but complemented where possible by physiological and epigenetic features. We will also examine transient cell populations present only during developmental stages, and we will retain positional information for all our cell data to create a developmental cell atlas that plots the diversity of cell types according to their locations in the growing human brain. We have developed innovative strategies for massively parallel profiling of molecular and physiological properties of primary human cortical cells using droplet based capture technologies, high content microscopy, and paired physiological responses to transcriptional state. We propose to conduct our integrated cellular survey of developing human brain in specific regions of the cortex, as well as in the striatum, thalamus, hypothalamus and cerebellum, and we will use single nuclei sequencing to unlock developmental time points that have been traditionally difficult to study. Our project will shed light on the origins of cellular diversity in the human cortex by addressing three specific aims: 1) We will use single cell RNA-sequencing to interrogate how neurogenesis and gliogenesis proceed and give rise to key cell types in the developed brain. We hypothesize that key events promoting regionalization and connectivity can be transcriptionally distinguished from the first trimester to postnatal stages, providing insights into how cell identity is determined. 2) Our developmental approach to the human brain cell atlas provides an opportunity to characterize transient cell populations that appear early in development in the marginal zone and subplate regions, and disappear at neonatal stages. These cell types are presumed to play important roles in establishing brain architecture and function, but they remain poorly characterized in developing human brain. We hypothesize the heterogeneity of these populations can be identified transcriptionally and can explain a diverse set of roles for these transient populations. 3) Transcriptional states are a powerful tool for cell type identification, but they do not capture the entire complexity of molecular features. We will profile cell-specific agonist responses and chromatin state that reflect heterogeneity within defined transcriptional classes. We hypothesize that the intersection of physiological state and epigenetic state to transcription will provide additional nuance to cell type classification. Our results will provide a framework of cellular taxonomy in the developing human brain and create a comprehensive cellular resolution map of molecularly defined cell types throughout functional regions of the human brain during development. This unique resource will serve as a blueprint for studies of human brain function, selective vulnerability of cell types in disease, and the features of brain evolution that make us unique.

Public Health Relevance

We plan to discover the building blocks of the developing human brain by identifying the specific cell types that are created during the critical stages of human brain development, and mapping their positions across space and time. The resulting high-resolution map will provide an unprecedented view of the developing human brain, and will serve as a necessary resource for understanding human-specific features of neurodevelopmental diseases such as autism and schizophrenia. The insights provided by this project cannot be modeled or discovered by studying animal models.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZMH1)
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Yao, Yong
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University of California San Francisco
Schools of Medicine
San Francisco
United States
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Nowakowski, Tomasz J; Bhaduri, Aparna; Pollen, Alex A et al. (2017) Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex. Science 358:1318-1323